Exenatide for the treatment of Alzheimer's Disease (AD). I continued to conduct a proof of concept Phase II, double blind, randomized, placebo-controlled, clinical trial to assess the safety and tolerability of exenatide treatment in participants with MCI/early AD. To this date, 30 participants have been enrolled, out of which 16 fulfilled inclusion criteria (clinical diagnosis of MCI/early AD, cerebrospinal fluid Ab(1-42) < 192 pg/dl) and were started on treatment with the study drug (exenatide or placebo). Eight participants completed the study, two participants were withdrawn from the study, and 6 continue treatment. Predictors and biomarkers of AD. In collaboration with NIA biostatistician, Larry Brant, I examined the performance of various physiological and laboratory measures followed longitudinally as predictors for AD. We found that longitudinal changes in blood pressure, lipids and depressive symptoms are significant predictors of future AD diagnosis with long lead times (the study is currently under review in the Journal of the American Geriatrics Society). In addition, I implemented a data reduction technique called Independent Component Analysis to structural MRI images of subjects with AD and MCI from ADNI and studied how patterns of structural covariance predict clinical diagnosis. This approach allowed us to classify subjects according to their future diagnosis with a high degree of accuracy (arguably, the highest ever achieved); the study is currently under review in the journal Neurobiology of Aging. In addition, I studied how peripheral insulin resistance is associated with regional brain glucose metabolism on FDG-PET in ADNI participants. We found that insulin resistance is associated with a maladaptive increase in metabolism at the hippocampus during the MCI stage, therefore, promoting AD pathogenesis (manuscript is currently under preparation). In collaboration with Dr. David Reiter, I have employed a novel Magnetic Resonance Spectroscopy (MRS) methodology at the NIA 3T MRI facility, which allows us to obtain in vivo measures on brain metabolites (glucose, lactate) and neurotransmitters (glutamate and GABA), which are relevant to AD pathogenesis. I conducted a study in healthy volunteers, in which I combined these measures with resting fMRI, which provides measures of brain functional connectivity, which showed a link between these neurotransmitter levels and brain connectivity. The study was pubmished in Neuroimage. In addition, based on MRS measures, I examined the association between brain glucose metabolism and neurotransmission; the study is currently under review in the journal Brain Research. I also examined the association between cognitive performance in AD and CSF inflammatory markers and found that higher CSF IL-12 predicts better cognition; this study is currently under review in the Journal of Neuroinflammation. Finally, I combined MRS and fMRI with CSF sampling to obtain Abeta and tau measures of brain amyloidosis and neurodegeneration. Preliminary (unpublished) results from these combined cross-sectional fMRI/MRS/CSF studies suggest the presence of associations between: glucose, lactate, glutamate and GABA in the precuneus; functional connectivity within the default mode network; and CSF biomarkers. Genetic and phenotypic characterization studies in Frontotemporal Lobar Degeneration. I collaborated with researchers from the National Institute of Neurological Disorders and Stroke and Texas Tech University to perform genetic studies in a closed Frontotemporal Dementia cohort. This last year, we published our findings of C9ORF72 expansions in our Frontotemporal Dementia cohort in Neurobiology of Aging. In addition, I contributed to a GWAS study in FTD, which is currently under review in Nature Genetics.